Scientists developed an AI monitoring agent to detect and stop harmful outputs

• Researchers from AutoGPT, Northeastern University, and Microsoft Research have developed a tool to monitor large language models (LLMs) for potentially harmful outputs.
• The tool can prevent harmful outputs, such as code attacks, from executing.
• Existing tools for monitoring LLM outputs often fall short when applied to models already in production on the open internet due to the dynamic intricacies of the real world.
• The researchers built a dataset of safe human/AI interactions and a competing dataset of adversarial outputs to train the monitoring agent.
• The agent achieved an accuracy factor of nearly 90% in distinguishing between innocuous and potentially harmful outputs.

The article discusses the development of a tool that aims to prevent harmful outputs from large language models. The sentiment is positive as it highlights the efforts of researchers to address potential risks associated with AI.